PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of diacareAmerican Diabetes AssociationSubscribeSearchDiabetes Care Journal
 
Diabetes Care. 2009 October; 32(10): 1901–1903.
Published online 2009 June 23. doi:  10.2337/dc09-0109
PMCID: PMC2752912

Effect of Glucose Variability on the Long-Term Risk of Microvascular Complications in Type 1 Diabetes

Eric S. Kilpatrick, MD, FRCPath,1 Alan S. Rigby, MSC,2 and Stephen L. Atkin, PHD, FRCP3

Abstract

OBJECTIVE

This study analyzed data from the Epidemiology of Diabetes Interventions and Complications (EDIC) study to see whether longer-term follow-up of Diabetes Control and Complications Trial (DCCT) patients reveals a role for glycemic instability in the development of microvascular complications.

RESEARCH DESIGN AND METHODS

The mean area under the curve glucose and the within-day glucose variability (SD and mean amplitude of glycemic excursions [MAGE]) during the DCCT were assessed to see whether they contributed to the risk of retinopathy and nephropathy by year 4 of the EDIC.

RESULTS

Logistic regression analysis showed that mean glucose during the DCCT and mean A1C during EDIC were independently predictive of retinopathy (each P < 0.001) as well as A1C during EDIC of nephropathy (P = 0.001) development by EDIC year 4. Glucose variability did not add to this (all P > 0.25 using SD or MAGE).

CONCLUSIONS

Glucose variability in the DCCT did not predict the development of retinopathy or nephropathy by EDIC year 4.

Analysis of the Diabetes Control and Complications Trial (DCCT) dataset has shown that glucose variability did not appear to be a further factor in the development or progression of either retinopathy or nephropathy (1,2). More recently, variability in A1C, a longer-term marker of glycemic control, during the DCCT has been found to add to the risk already indicated by the mean A1C value (3).

This current study has examined data from the first 4 years of the DCCT extension study, the Epidemiology of Diabetes Interventions and Complications (EDIC) study. The EDIC has already shown the long-term beneficial effects of intensive treatment on microvascular complications (46). Our goal was to establish whether the follow-up study also unearths a longer-term relationship between glucose variability during the DCCT and subsequent retinopathy and nephropathy.

RESEARCH DESIGN AND METHODS

We used the publicly accessible datasets stored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) relating to both the DCCT and the first 4 years of the EDIC study. After an average period of 6.5 years enrollment in the DCCT, patients were offered intensive glucose management and were asked to continue with follow-up as part of the EDIC study (7).

Retinopathy development and progression was defined as a ≥3-unit change in the 25-point Early Treatment Diabetic Retinopathy Study (ETDRS) score measured at baseline and in all patients completing year 4 in the EDIC (n = 1,208), as well as in a subset of patients at years 1 (n = 369), 2 (n = 447), and 3 (n = 419). Nephropathy was defined as an albumin excretion rate >40 mg/day.

A seven-point blood glucose profile was requested to be taken throughout the day at three monthly intervals during, but not beyond, the DCCT. Mean blood glucose (area under the curve) and glucose variability (SD and mean amplitude of glycemic excursions [MAGE] [8]) during the DCCT were calculated as published previously (9). Results were virtually identical for the blood glucose profiles based on five or more readings and are not considered further.

Statistical methods

We used the generalized estimating equation with a logit link to assess the effect of covariates on the odds of development or progression of retinopathy and nephropathy over repeated time points (10,11) using the Stata statistical computer package (12). Wald robust estimates of SE were used to estimate 95% CIs. The two treatment groups (intensive versus conventional) were analyzed separately and combined. Models were adjusted as described in Table 1.

Table 1
Longitudinal multiple logistic regression models for microvascular complications

RESULTS

Patients with a three-step or more change in the ETDRS at years 1, 2, 3, and 4 were 15 of 369 (4%), 37 of 443 (8%), 47 of 419 (11%), and 146 of 1,208 (12%), respectively. A total of 115 of 1,343 (9%) patients had an ETDRS score ≥3 at EDIC baseline. Patients with nephropathy (albumin excretion rate >40 mg/day) at years 3 and 4 were 184 of 1,302 (14%). The mean ± SD variability of glucose was 4.11 ± 0.88 and 8.01 ± 2.00 mmol/l for SD and MAGE, respectively.

There was no significant relationship between blood glucose variability in the DCCT and the development or progression of retinopathy in EDIC after adjustment (Table 1). Associations between nephropathy and glycemia were generally less strong than those for retinopathy, with the exception of A1C at eligibility. Our focus has been on new events since the end of the DCCT. A separate analysis taking any event, irrespective of the time of event, from the DCCT up to and including the EDIC showed that there was no significant relationship with blood glucose variability (data not shown).

CONCLUSIONS

This analysis has extended the follow-up of DCCT patients to year 4 of the EDIC study and found no evidence, or even a signal, that this uncovers a role for glucose variability in adding to the risk of retinopathy and nephropathy already predicted by the mean glucose alone.

This finding is consistent with two analyses of events in the DCCT alone, which seemingly showed glucose variability to be of little relevance to complication risk (1,2). However, variations in A1C (as opposed to glucose) around a mean A1C value do indeed seem to predict small vessel complications, raising the possibility either that long-term fluctuations in glycemia are more important than short-term ones or that A1C was more sensitive in detecting glycemic variability than the method used to assess mean glucose in the DCCT (3). An additional observation is that A1C at the start of the DCCT, which was a strong predictor of retinopathy during the DCCT, was not such a good predictor in this analysis of EDIC. This may be an earlier indication of the waning effect of metabolic memory described recently in respect to the legacy effect that A1C during the DCCT had on retinopathy by year 10 of EDIC (13).

There are limitations to this study, with the most important being the lack of glucose profiling during EDIC and the inability to precisely evaluate diurnal glycemic variation from quarterly seven-point glucose profiles. Regarding the first limitation, we determined this analysis should regard glucose variability during the DCCT as one of the baseline covariates at the start of EDIC. With respect to glycemic control throughout EDIC, we have also accounted for A1C during the extension study, and it is reassuring that all patients were offered the same intensive treatment during this period. Counterbalancing any limitations are the size of the DCCT/EDIC dataset (e.g., there was more than 22,000 seven-point glucose profiles during the DCCT) and the fact that the study is, in many respects, impossible to reproduce because it was performed in an era when possible confounding factors, such as the use of antihypertensive, antiplatelet, and lipid-lowering agents, were not in routine use.

In summary, increasing the follow-up period of DCCT patients to year 4 of EDIC has not unearthed an association between glucose variability and microvascular complication risk that adds to that already predicted by a patient's mean glucose value.

Acknowledgments

This research has been supported by a project grant (BDA:RD07/0003461) from Diabetes UK.

This research was also supported by an unrestricted educational grant from Novo Nordisk. No other potential conflicts of interest relevant to this article were reported.

Parts of this study were presented at the Diabetes UK Annual Professional Conference, Glasgow, U.K., 11–13 March 2009.

We thank the DCCT/EDIC investigators for making their trial dataset public and therefore allowing independent investigators to analyze their work for the benefit of patients with type 1 diabetes.

Footnotes

The DCCT and its follow-up, the EDIC study, were conducted by the DCCT/EDIC Research Group and supported by National Institutes of Health (NIH) grants and contracts and by the General Clinical Research Center Program, National Center for Research Resources. This article was not prepared under the auspices of the DCCT/EDIC study and does not represent analyses or conclusions of the DCCT/EDIC study group or NIH.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

References

1. Service FJ, O'Brien PC.: The relation of glycaemia to the risk of development and progression of retinopathy in the Diabetic Control and Complications Trial. Diabetologia 2001;44:1215–1220 [PubMed]
2. Kilpatrick ES, Rigby AS, Atkin SL.: The effect of glucose variability on the risk of microvascular complications in type 1 diabetes. Diabetes Care 2006;29:1486–1490 [PubMed]
3. Kilpatrick E, Rigby A, Atkin S.: A1C variability and the risk of microvascular complications in type 1 diabetes: data from the Diabetes Control and Complications Trial. Diabetes Care 2008;31:2198–2202 [PMC free article] [PubMed]
4. The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. Retinopathy and nephropathy in patients with type 1 diabetes four years after a trial of intensive therapy. N Engl J Med 2000;342:381–389 [PMC free article] [PubMed]
5. The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. Effect of intensive therapy on the microvascular complications of type 1 diabetes mellitus. JAMA 2002;287:2563–2569 [PMC free article] [PubMed]
6. The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: the Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA 2003;290:2159–2167 [PMC free article] [PubMed]
7. The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. Epidemiology of Diabetes Interventions and Complications (EDIC): design, implementation, and preliminary results of a long-term follow-up of the Diabetes Control and Complications Trial cohort. Diabetes Care 1999;22:99–111 [PMC free article] [PubMed]
8. Service FJ, Molnar GD, Rosevear JW, Ackerman E, Gatewood LC, Taylor WF.: Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes 1970;19:644–655 [PubMed]
9. Kilpatrick ES, Rigby AS, Atkin SL.: Mean blood glucose compared with HbA1c in the prediction of cardiovascular disease in patients with type 1 diabetes. Diabetologia 2008;51:365–371 [PubMed]
10. Liang K, Zeger S.: Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13–22
11. Diggle PJ, Heagerty P, Liang K-Y, Zeger SL.: Analysis of Longitudinal Data. New York, Oxford University Press, 2002
12. Horton N, Lipsitz S.: Review of software to fit generalized estimating equation regression models. The American Statistician 1999;53:160–169
13. White NH, Sun W, Cleary PA, Danis RP, Davis MD, Hainsworth DP, Hubbard LD, Lachin JM, Nathan DM.: Prolonged effect of intensive therapy on the risk of retinopathy complications in patients with type 1 diabetes mellitus: 10 years after the Diabetes Control and Complications Trial. Arch Ophthalmol 2008;126:1707–1715 [PMC free article] [PubMed]

Articles from Diabetes Care are provided here courtesy of American Diabetes Association